By: Steven Ramirez, Conference Co-Chair of Text Analytics World Chicago
In anticipation of his upcoming conference co-presentation, Personalized Medicine and Text Analytics at Text Analytics World Chicago, June 21-22, 2016, we asked Dirk Van Hyfte, Senior Advisor for Biomedical Informatics at InterSystems Corporation, a few questions about his work in text analytics.
Q: In your work with text analytics, what behavior or outcome do your models predict?
A: To support the shift from reactive to pro-active medicine we look for patients who are at risk to develop Sepsis, Hepatitis C and Delirium. In the area of Behavioral Health we support harm reduction projects.
Q: How does text analytics deliver value at your organization – what is one specific way in which it actively drives decisions or operations?
A: The ability to effectively harness the mountains of unstructured data in healthcare is a key strategic asset for any successful organization.
Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?
A: One California IDN has demonstrated great success in reducing sepsis mortality, bringing it down from 55% at the start of their interventions to a current level of 35%. In an effort to bring sepsis mortality down even further to 25%, this IDN is now piloting the use of Text Analytic Tools to add unstructured data analysis to its armamentarium.
Q: What surprising discovery or insight have you unearthed in your data?
A: There are huge gaps in structured data fields. At a Cancer Registry we identified a data gap of 22% where HER-2 testing had been ordered but no definite outcome was recorded. The organization was able to identify a systematic shortfall in the availability of results and was able to investigate this.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Text Analytics World.
A: Numerous case studies, a few of which have been discussed above, have demonstrated the shortcomings of structured data. Important information, such as disease risk factors, might not exist within structured data at all, and even when the appropriate structured data field exists within a data model, the data can be missing or unavailable. Unstructured data, which comprises perhaps 80% of all healthcare data, has great potential to replace that missing structured data and/or complement what’s already there.
Don't miss Dirk’s conference co-presentation, Personalized Medicine and Text Analytics on Wednesday, June 22, 2016 from 3:30 to 4:00 pm at Text Analytics World Chicago. Click here to register to attend.